Racial and ethnic determinants of Covid-19 risk · 6/18/2020 · 2 ABSTRACT Background Racial and...

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Racial and ethnic determinants of Covid-19 risk Chun-Han Lo, M.D.1,2,3*, Long H. Nguyen, M.D.1,2,4*, David A. Drew, Ph.D.1,2*, Mark S. Graham, Ph.D.5*, Erica T. Warner, Sc.D.1,6, Amit D. Joshi, Ph.D.1,2, Christina M. Astley,

Sc.D.7,8, Chuan-Guo Guo, M.S.1,2,9, Wenjie Ma, Sc.D.1,2, Raaj S. Mehta, M.D.1,2,4, Sohee Kwon, M.D.1,2, Mingyang Song, Sc.D.1,2,3,10, Richard Davies, M.A.11, Joan

Capdevila, P.hD.11, Karla A. Lee, MBBCh12, Mary Ni Lochlainn, MBBCh12, Thomas Varsavsky, M.Sc.5, Carole H. Sudre, Ph.D.5, Jonathan Wolf, B.Sc.11, Yvette C. Cozier,

D.Sc.16, Lynn Rosenberg, Ph.D.16, Lynne R. Wilkens, Dr.P.H.13, Christopher A. Haiman, Sc.D.14,15, Loïc Le Marchand, Ph.D.13, Julie R. Palmer, Sc.D.16, Tim D. Spector, M.D.12, Sebastien Ourselin, Ph.D.5, Claire J. Steves, Ph.D.12, Andrew T. Chan, M.D.1,2,8,17 on

behalf of the COPE Consortium *Contributed equally to this work

1 Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; 2 Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; 3 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, U.S.A.; 4 Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, U.S.A.; 5 School of Biomedical Engineering & Imaging Sciences, King’s College London, London, U.K.; 6 Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Massachusetts General Hospital, Boston, Massachusetts, U.S.A.; 7 Computational Epidemiology Lab and Division of Endocrinology, Boston Children’s Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; 8 Broad Institute of Harvard and MIT, Cambridge, Massachusetts, U.S.A.; 9 Department of Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China; 10 Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, U.S.A.; 11 Zoe Global Limited, London, U.K.; 12 Department of Twin Research and Genetic Epidemiology, King’s College London, London, U.K.; 13 Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A.; 14 Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, California, U.S.A.; 15 Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California, U.S.A.; 16 Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; 17 Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health. Boston, Massachusetts, U.S.A. CORRESPONDANCE

Andrew T. Chan, M.D., M.P.H. Massachusetts General Hospital and Harvard Medical School 100 Cambridge Street, 15th Floor Boston, Massachusetts 02114, U.S.A. [email protected] WORD COUNT: 2700 words; 4 tables; 1 figure.

. CC-BY-NC-ND 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)

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ABSTRACT

Background

Racial and ethnic minorities have disproportionately high hospitalization rates and

mortality related to the novel coronavirus disease 2019 (Covid-19). There are

comparatively scant data on race and ethnicity as determinants of infection risk.

Methods

We used a smartphone application (beginning March 24, 2020 in the United Kingdom

[U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants

who reported their race/ethnicity through May 25, 2020 and employed logistic

regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals

(CIs) for a positive Covid-19 test among racial and ethnic groups.

Results

We documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic

white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian;

and 347 among 63,653 other racial minority participants. Compared with non-Hispanic

white participants, the risk for a positive Covid-19 test was increased across racial

minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices

and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated

but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56

[1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern

participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or



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receiving treatment was also observed for several racial/ethnic minority subgroups.

Conclusions

Our results demonstrate an increase in Covid-19 risk among racial and ethnic minorities

not completely explained by other risk factors for Covid-19, comorbidities, and

sociodemographic characteristics. Further research investigating these disparities are

needed to inform public health measures.



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INTRODUCTION

The novel coronavirus disease 2019 (Covid-19) caused by the severe acute respiratory

syndrome coronavirus 2 (SARS-CoV-2) continues to pose a tremendous threat to the

global community. As of June 2020, over 6.4 million cases of Covid-19 have been

documented worldwide with nearly 381,000 deaths.1 Prior investigations suggest that

Covid-19 disproportionately impacts certain populations, including older individuals,

males,2 and those diagnosed with obesity3 or other underlying health conditions.4

However, large-scale studies investigating potential racial or ethnic disparities in

infection risk are limited.

Emerging data in the United States (U.S.) and the United Kingdom (U.K.) suggest that

racial and ethnic minorities may account for an outsized proportion of Covid-19

hospitalizations and deaths.5–8 Although the U.S. Center for Disease Control and

Prevention (CDC) recently began mandating the reporting of Covid-19 testing results

according to race/ethnicity,9 data on the risk of testing positive for Covid-19 across a

large population are lacking. Most estimates of Covid-19 risk to date are based on

reports that are not uniformly collected, rely on a patchwork of information from local

authorities, and do not account for other factors that could influence risk,10 such as

comorbidities3,11, ability to practice social distancing,12,13 income disparity, poorer access

to testing/care, and language and cultural barriers.14–16

Given the importance of understanding the determinants of health among ethnic

minority groups, a comprehensive multinational investigation examining racial and



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ethnic disparities in risk of Covid-19 infection is urgently needed. We conducted a

population-scale investigation to examine the risk of reporting a positive SARS-CoV-2

test and presenting for Covid-19 care among racial and ethnic groups in the U.S and the

U.K.

METHODS

Real-time assessment of Covid-19 using smartphone technology

We recruited individuals from the general population in the U.S. and the U.K. using the

Covid Symptom Study smartphone application (“app”) developed by Zoe Global Ltd.

with scientific input from Massachusetts General Hospital and King’s College London.17

The app was launched in the U.K. on March 24 and in the U.S. March 29, 2020. It offers

users a guided interface to report baseline demographic information and comorbidities.

Users are prompted to use the application daily to allow for longitudinal, prospective

collection of concomitant symptoms, health care visits, and Covid-19 test results. Study

participants were recruited through general media, social media outreach, and direct

invitations from the investigators of long-running prospective cohorts.18 At enrollment,

participants provided informed consent to the use of aggregated information for

research purposes and agreed to applicable privacy policies and terms of use. This

research study was approved by the Partners Human Research Committee (Protocol

2020P000909) and King’s College London Ethics Committee (REMAS ID 18210, LRS-

19/20-18210). This protocol is registered with ClinicalTrials.gov (NCT04331509).

Assessment of risk factors, symptoms, testing, and/or care for Covid-19



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Information collected through the application has previously been described.17 Briefly, at

enrollment, participants were asked to provide information on demographic factors and

suspected risk factors for Covid-19 (Table 1). On first use and daily, participants were

asked if they felt physically normal, and if not, their symptoms, including the presence of

fever, persistent cough, fatigue, and loss of smell/taste, among others (Supplemental

Table 2 & Supplemental Table 3). Participants were asked if they had been tested for

Covid-19 and the results (none, negative, pending, or positive). Visits to the hospital for

care were documented by participants during daily logs and were recorded if they

reported being “in hospital” or “back from hospital”. Treatment was recorded if

participants indicated receiving any of the following: supplemental oxygen, invasive

ventilation, fluids, inhalers, or other treatment.

Assessment of race and ethnicity

Individuals were asked to report with which race and/or ethnicity they self-identified.

Questions were based on standard categories from the U.S. National Institutes of

Health (NIH)19 and the U.K. Office for National Statistics.20 (Supplemental Table 1).

Individuals who identified their race or ethnicity as “Other” were provided an option to

enter a free-text description. Additional categories created for the U.K. include

“East/Southeast Asian” and “Hispanic/Latinx”. Individuals who identified as “Mixed Race”

or selected more than one race were described as “More than one race” and grouped

with “Other”. We excluded participants who did not provide information on racial or

ethnic identity or selected “prefer not to say”. In pooled analyses, categories in the U.S.

and the U.K. were harmonized according to NIH categories.19 “White” and



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“Hispanic/Latinx” were categorized separately and those who were “Non-Hispanic white”

were the referent group for all analyses. “Native Hawaiian and Pacific Islanders'', “South

Asian”, “Chinese”, and “East/Southeast Asian” were grouped as “Asian”, while

“American Indian or Alaskan Natives” and “Middle Eastern” was categorized as “Other”

(Supplemental Methods).

Socioeconomic and population density factors

Population density was calculated from census data for each Zip Code Tabulation Area

(ZCTA) in the U.S. and Lower Layer Super Output Area (LSOA) in the U.K. In the U.S.,

we obtained indicators of income and education according to Zip Code from the U.S.

Department of Agriculture.21 Comparable socioeconomic indices were quantified using

the indices of multiple deprivation (IMD) at the LSOA level in the U.K.,22 for which we

combined scores from each of the U.K.'s 4 constituent countries into a unified scale by

assuming the same distribution of deprivation scores in each country.

Statistical analysis

We employed logistic regression models to examine the odds ratios (ORs) and 95%

confidence intervals (CIs) of a positive Covid-19 test and of seeking and receiving

treatment. Multivariable models were conditioned upon age, date, and country (if

pooled). Additional covariates were selected a priori based on putative risk factors,

including sex, body mass index, history of diabetes, heart, lung, or kidney disease,

current smoking status, isolation, community interaction with individuals with Covid-19,

frontline healthcare worker status, population density, income, and education. Missing



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categorical data were included as a missing indicator. To account for likelihood to

receive testing, we performed separate inverse probability weighting (IPW) in the U.S.

and the U.K. as a function of race/ethnicity and other factors, such as age, symptom

burden, COVID-19 exposure risk factors, and socioeconomic status, followed by inverse

probability weighted logistic regression (Supplemental Methods).

In addition to a positive Covid-19 test, we utilized a previously developed symptom-

based classifier predictive of positive Covid-19 testing.23 Briefly, using logistic regression

and symptoms preceding testing, we found that a weighted score including loss of

smell/taste, fatigue, persistent cough, and loss of appetite predicts Covid-19 positivity

with high specificity (Supplemental Methods). To further examine the risk of more

severe Covid-19, we evaluated the likelihood of Covid-19 and hospital visit or treatment.

We conducted analyses in the U.S. and the U.K. separately but also leveraged

harmonized data for pooled results. Two-sided p-values <0.05 were considered

statistically significant. All analyses were performed using R 3.6.1 (Vienna, Austria).

RESULTS

Study population

Between March 24 and May 25, 2020, 2,414,601 participants (U.S. n = 179,873; U.K. n

= 2,234,728) had registered and responded to questions within the app, including

2,259,841 non-Hispanic white, 9,615 Hispanic, 18,176 Black, 63,316 Asian participants,

and 63,653 participants of more than one race/other race. Median age was 47 years

(interquartile range [IQR] 33-60). Black and Hispanic participants were more likely to be



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overweight or obese and have diabetes and kidney disease (Table 1). All racial and

ethnic minorities reported a lower level of social isolation, were comparatively

overrepresented among frontline healthcare workers, and reported a higher likelihood of

exposure to individuals with suspected or documented Covid-19. Non-Hispanic white

participants more commonly reported living in less densely populated regions, and

Black individuals tended to live in locales characterized by lower income and

educational attainment. The prevalence of symptoms appeared largely consistent

across groups (Supplemental Table 2 & Supplemental Table 3). The most common

symptoms reported were headache, fatigue, and sore throat.

Risk of a positive Covid-19 test according to race and ethnicity

Among 2,414,601 adults, we documented 10,051 reports of positive Covid-19 testing. In

the U.S., all racial minorities had an increased risk of reporting a positive Covid-19 test

(age-adjusted ORs ranging from 1.52 to 3.69), with the highest risk among Black

participants (Table 2a). In the U.K., increased risk was observed among Black, South

Asian, East/Southeast Asian, Middle Eastern individuals, and those reporting more than

one or other race (age-adjusted ORs ranging from 1.23 to 2.85) (Table 2b). Results

were essentially unchanged with additional adjustment for comorbidities and lifestyle

factors. We next performed IPW to account for the likelihood of receiving a test and

found modest attenuation of the estimates, with most racial and ethnic minorities

remaining significantly associated with a positive test for Covid-19.

Next, we considered the possibility that other social determinants mediated the



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association of race and ethnicity with risk of Covid-19 by adjusting for income and

education, population density, level of isolation, frontline healthcare worker status, and

community exposure to a Covid-19-positive individual (Figure 1). Overall, the

associations (aOR [95% CI]) were moderately attenuated but remained significant for

Hispanic (1.58 [1.24-2.02]) and Black users (2.56 [1.93-3.39]) in the U.S. and South

Asian (1.52 [1.38-1.67]) and Middle Eastern populations (1.56 [1.25-1.95]) in the U.K.

Risk of predicted Covid-19 using a symptom-based classifier

To further address the possibility of disparities in access to testing, we used a validated

symptom-based model associated with predicted Covid-19 infection in a pooled analysis.

Compared to non-Hispanic white participants, we found a significant increase in risk for

predicted Covid-19 in Black (aOR 1.17 [95% CI 1.10-1.25]), Hispanic (1.11 [1.00-1.23]),

Asian (1.06 [1.03-1.10]), and more than one/other racial minorities (1.21 [1.17-1.25])

(Table 3). Within each country, we observed similar estimates for combined racial and

ethnic minority groups compared to non-Hispanic whites in the U.S. (1.20 [1.11-1.30])

and the U.K. (1.22 [1.19-1.25]) (data not shown).

Risk of Covid-19, seeking, or receiving treatment

In both the U.S. and the U.K, compared to non-Hispanic white participants, the aORs

(95% CI) for Covid-19 requiring a hospital visit were elevated across racial and ethnic

minorities, ranging from 1.32 (1.03-1.68) for more than one/other race to 1.64 (1.20-2.23)

for Black race (Table 4). The corresponding aORs (95% CI) for receiving treatment

were also increased for Black (1.83 [1.17-2.85]) and Asian participants (1.60 [1.19-



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2.14]). Country-specific estimates for combined minority groups compared to non-

Hispanic whites were similar to the pooled analysis (Supplemental Table 4 &

Supplemental Table 5).

DISCUSSION

Among 2,414,601 participants, we observed that ethnic and racial minorities, particularly

Black and Hispanic individuals in the U.S. and Asian and Middle Eastern individuals in

the U.K., had a greater risk of testing positive for Covid-19 compared to non-Hispanic

white participants. Results were essentially unchanged after adjusting for comorbid

conditions. While further adjustment for socioeconomic indices and Covid-19 risk factors

attenuated the associations, the risks remained significantly elevated for these

minorities. These results were consistent after adjusting for the likelihood of being

tested or when examining predicted Covid-19 infection based on prevalent symptoms.

Racial minorities also had a modestly increased risk of Covid-19 and seeking hospital-

based evaluation/treatment.

The racial and ethnic disparities reported here are consistent with studies documenting

racial and ethnic differences in Covid-19 outcomes.5,7,24 Our data provide further

support of research from the U.S. state of Louisiana showing that Black race was

associated with a nearly 2-fold increased odds of hospital admission among Covid-19

patients after adjusting for comorbidities and sociodemographic factors.24 Similarly, a

study from Public Health England demonstrated that the highest age-standardized

death rates in confirmed Covid-19 cases were among people of Black ethnic groups,



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followed by Asian and mixed ethnic groups in the U.K., even after accounting for

demographics, social deprivation, and region7. Although these data support a

consistently higher risk of worsened Covid-19 outcomes among racial and ethnic

minorities, whether the risk of infection also differs by race and ethnicity among the

general community warrants further research. Increasing reports from the U.S. CDC,

local state health departments,25,26 and numerous governmental agencies in Europe

suggest a greater risk of Covid-19 among communities of color,7 but do not generally

account for other factors that could influence the risk of infection.10 Our study

complements these early reports, and by accounting for Covid-19 exposure risk factors,

sociodemographic information, and comorbidities, our investigation better defines the

magnitude of increased risk among ethnic and racial minorities compared to non-

Hispanic white participants.

Our results demonstrate that comorbid conditions do not explain the increased

likelihood to test positive for Covid-19 among minority populations, especially in the U.S.,

highlighting the considerable role of structural inequalities in elevating risk. Communities

of color may be less able to effectively practice social distancing,27 given prior literature

suggesting they are highly represented among the essential workforce28 and live in

neighborhoods with the higher SARS-Cov-2 infection rates.29 We were able to show

some attenuation of Covid-19 risk when accounting for income, education, population

density, measures of social isolation, occupation as a healthcare worker, and exposure

to a community member with Covid-19. However, after adjustment, the risk of a positive

Covid-19 test remained significant for several racial and ethnic minorities, which is likely



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due to additional contributing factors for which we were unable to account, including

insurance coverage, access to healthcare, use of public transit, and other essential

occupations not specifically queried. Asian and Hispanic populations are also more

likely than non-Hispanic whites to live in multigenerational households,30 and, like Black

populations, are more likely to live in densely populated urban areas.31 Moreover, in the

U.S. due to residential segregation, racial and ethnic minorities may live in

predominantly minority neighborhoods with higher prevalence of infection, thereby

increasing their risk of coming into contact with infected members of the community.29

Furthermore, Asian and Hispanic populations represent a higher proportion of foreign-

born individuals,30 which poses additional challenges associated with cultural and

language barriers, misinformation, immigration-related fear, and anxiety related to

accessing care.32,33 Finally, “weathering” or chronic stress related to structural racism

contributes to accelerated aging and chronic diseases that may contribute to COVID-19

risk.34

The strengths of this study include the use of a smartphone application to rapidly collect

prospective data from a large multinational and multiethnic cohort, which offers real-time,

actionable Covid-19 risk estimates to inform the public health response to an ongoing

pandemic. Second, our study design examined documented, self-reported Covid-19

cases in the general smartphone user population, overcoming limitations related to

capturing only more severe cases through administrative hospitalization records or

death reports. Third, we examined the risk of predicted Covid-19 according to racial and

ethnic groups and found results largely consistent with those of self-reported Covid-19.



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This approach was not dependent on differences in testing availability which might vary

across racial and ethnic groups. Finally, we collected information on and adjusted for a

wide range of known or suspected risk factors for Covid-19, which are generally not

available in existing registries or population-scale surveillance efforts.

Our study has several limitations. While the use of syndromic surveillance to better

understand Covid-19 disparities has great strengths in flexibility, speed and sample size,

this methodology is largely dependent upon self-reported data, and therefore

susceptible to measurement bias, residual confounding bias, and selection (collider)

bias. The probability of app participation, reporting, or access may be differential

according to Covid-19 outcomes, minority status and/or covariates.35,36 Smartphone-

based tools may preclude participation of certain populations such as elderly, low-

income, or non-English speakers. Although our study had a relatively small proportion of

racial-ethnic minorities compared to census estimates, we enrolled a high absolute

number of individuals for most racial ethnic groups, with the notable exception of Native

Americans. We attempted to mitigate selection bias through IPW and confounding

through multivariable adjustment. Measurement errors in self-reported participant

characteristics are possible. Future research may validate some risk factors in

longitudinal studies linked to the Covid Symptom Study (e.g. Nurses’ Health Study).

Finally, variables in the app were limited in scope to optimize participation. We

acknowledge that the assessed racial and ethnic groups may be oversimplifications,

and do not completely characterize the true heterogeneity in how participants

experience race and ethnicity.



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In conclusion, within a large population-based sample of individuals in the U.S. and the

U.K., we demonstrate a significantly increased risk of Covid-19 and hospital-based

evaluation/treatment for Covid-19 among several racial and ethnic minorities compared

to non-Hispanic white individuals, which was partially explained by risk factors for

exposure and traditional sociodemographic factors. Our results confirm the

comparatively outsized burden of Covid-19 on ethnic and racial minorities and the need

for further research to understand the basis for these health inequalities.

ACKNOWLEDGEMENTS

We express our sincere thanks to all of the participants who entered data into the app,

including study volunteers enrolled in cohorts within the Coronavirus Pandemic

Epidemiology (COPE) consortium. We thank the staff of Zoe Global Ltd., the

Department of Twin Research at King’s College London, and the Clinical and

Translational Epidemiology Unit at Massachusetts General Hospital for their tireless

work.

CONFLICT OF INTEREST

TJW, RD, and JC are employees of Zoe Global Ltd. TDS is a consultant to Zoe Global

Ltd. DAD and ATC previously served as investigators on a clinical trial of diet and

lifestyle using a separate mobile application that was supported by Zoe Global Ltd.

Other authors have no conflict of interest to declare.



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FUNDING

Zoe provided in kind support for all aspects of building, running and supporting the app

and service to users worldwide. LHN is supported by the American Gastroenterological

Association Research Scholars Award. DAD is supported by the National Institute of

Diabetes and Digestive and Kidney Diseases K01DK120742. ATC is the Stuart and

Suzanne Steele MGH Research Scholar and Stand Up to Cancer scientist. The

Massachusetts Consortium on Pathogen Readiness (MassCPR) and Mark and Lisa

Schwartz supported MGH investigators (LHN, DAD, ADJ, CGG, WM, RSM, CHL, SK,

ATC). King’s College of London investigators (KAL, MNL, TV, MG, CHS, MJC, SO, CJS,

TDS) were supported by the Wellcome Trust and EPSRC (WT212904/Z/18/Z,

WT203148/Z/16/Z, T213038/Z/18/Z), the NIHR GSTT/KCL Biomedical Research Centre,

MRC/BHF (MR/M016560/1), UK Research and Innovation London Medical Imaging &

Artificial Intelligence Centre for Value Based Healthcare, and the Alzheimer’s Society

(AS-JF-17-011). MNL is supported by an NIHR Doctoral Fellowship (NIHR300159).

CMA is supported by the NIDDK (K23 DK120899) and the Boston Children’s Hospital

Office of Faculty Development Career Development Award. The Multiethnic Cohort

investigators (LRW. CAH, LLM) were supported by grant U01 CA164973. Sponsors had

no role in study design, analysis, and interpretation of data, report writing, and the

decision to submit for publication. The corresponding author had full access to data and

the final responsibility to submit for publication.

DATA AVAILABILITY

Data collected in the app are being shared with other health researchers through the



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NHS-funded Health Data Research UK (HDRUK)/SAIL consortium, housed in the UK

Secure e-Research Platform (UKSeRP) in Swansea. Anonymized data collected by the

Covid Symptom Study app can be shared with bonafide researchers via HDRUK,

provided the request is made according to their protocols and is in the public interest

(see https://healthdatagateway.org/detail/9b604483-9cdc-41b2-b82c-14ee3dd705f6).

US investigators are encouraged to coordinate data requests through the COPE

Consortium (www.monganinstitute.org/cope-consortium). Data updates can be found at

https://covid.joinzoe.com.

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Jun 15]. Available from:

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Table 1a. Baseline characteristics of study participants in the United Statesa Race/Ethnicityb

White, Non-

Hispanic (n=147325)

Hispanic/Latinx (n=9251)

Black (n=4977)

Asian (n=6828)

More than one race/Other race

(n=4774)

Prefer not to say (n=2044)

Age, year, % < 25 7.9 17.1 9.1 9.0 21.0 7.7 25-34 8.6 16.0 7.3 12.3 12.0 10.0 35-44 12.9 19.3 10.1 15.8 15.5 15.3 45-54 14.5 16.5 18.1 15.7 14.0 17.0 55-64 20.6 13.6 24.9 12.0 14.5 19.8 ≥ 65 35.6 17.5 30.4 35.2 23.0 30.2 Male sex, % 36.8 40.7 29.1 43.1 37.4 37.4 BMI, kg/m2, % 17-18.4 4.2 5.9 3.3 6.5 9.4 5.9 18.5-24.9 40.2 35.5 22.8 54.0 36.6 40.8 25-29.9 32.0 31.0 32.4 29.4 28.5 32.4 ≥ 30 23.6 27.6 41.4 10.1 25.5 20.9 Comorbidities, % Diabetes 5.7 6.9 13 8.8 6.4 5.0 Heart disease 6.5 4.4 5.9 6.5 5.9 6.2 Lung disease and asthma 12.6 13.3 14.8 10.1 16.8 11.5 Kidney disease 1.5 1.3 2.4 1.8 1.8 1.1 Cancerb 2.3 1.3 1.8 1.9 1.7 1.6 Pregnant (% of females) 0.5 0.9 0.2 0.6 0.5 0.2 Medication usage, % Immunosuppressants 3.8 3.0 5.0 2.9 4.0 3.3 Chemo/Immunotherapy 0.5 0.4 0.6 0.5 0.5 0.4 ACE inhibitor 10.7 7.5 12.3 6.9 8.5 8.2 Aspirinb/NSAIDs 15.9 12.9 12.9 5.8 13.8 13.2 Current smokerb, % 5.0 7.4 8.3 4.0 7.9 4.5 Isolation, % Never left home 6.1 8.9 9.5 5.6 6.1 4.7 Rarely left home 88.7 81.4 82.5 85.8 86.0 88.9 Often left home 5.3 9.8 8.1 8.6 7.9 6.5 Frontline healthcare worker, % 8.0 8.7 9.2 8.9 7.2 6.5 Community exposure, % Documented 4.0 6.6 7.7 4.4 5.2 4.3 Suspected 5.3 6.7 5.0 4.1 6.8 5.0 Population density, people per sq kmc

3823.9 [1074.9, 9670.5]

7503.2 [2231.5, 16392.8] 7368.3 [3078.7, 16588.6] 7924.6 [4074.3, 17256.8] 5416.2 [1452.5, 12761.6] 4889.1 [1278.4, 11779.3]

Income and education Median income, USD 67986 [58375,

83591] 67986 [58037,

81061] 66793 [57200, 78777] 82808 [67986, 89373] 69475 [59838, 83695] 67986 [59114, 84213] % with Bachelor’s degree 35.9 [29.3, 44.8] 33.1 [28.8, 42.2] 34.1 [29.7, 43.2] 34.7 [31.8, 46.3] 34.3 [29.6, 44.8] 35.4 [29.7, 44.8] Abbreviations: ACE, angiotensin converting enzyme; BMI, body mass index; km, kilometer; kg, kilogram; NSAIDs, non-steroidal anti-inflammatory drugs. aMedian [IQR] is presented for continuous variables. Frequencies and proportions are calculated based on the total number of participants with available data. bHistory of cancer, aspirin use, and smoking status have been queried since launch in the U.S. and since 3/29/2020 in the U.K. Race and ethnicity questions were queried as of 4/18/2020. cPopulation density was calculated from census data for each Zip Code Tabulation Area.

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Table 1b. Baseline characteristics of study participants in the United Kingdoma Race/Ethnicityb

White, non-

Hispanic (n=2104829)

Hispanic/Latinx (n=2379)

Black (n=13057)

South Asian (n=46350)

Chinese (n=7736)

East/Southeast Asian

(n=2110)

Middle Eastern (n=8466)

More than one race/other race

(n=48908)

Prefer not to say (n=8893)

Age, year, % < 25 13.0 9.3 12.6 12.7 12.0 6.9 11.6 30.1 10.9 25-34 14.4 23.5 17.2 18.7 23.0 16.5 19.8 18.9 15.8 35-44 17.7 33.6 22.2 27.9 27.6 30.1 25.8 19.1 22.0 45-54 20.2 20.2 23.8 20.7 19.9 28.1 18.9 15.1 22.2 55-64 18.7 8.8 18.5 11.8 10.2 11.2 13.6 10.8 16.9 ≥ 65 16.0 4.5 5.7 8.2 7.3 7.3 10.3 6.1 12.2 Male sex, % 41.3 36.8 46.1 46.7 34.8 25.5 50.8 41.4 49.5 BMI, kg/m2, % 17-18.4 5.6 5.5 5.9 7.0 8.3 6.7 5.1 12.9 7.5 18.5-24.9 41.5 44.2 29.8 46.3 64.8 61.0 41.6 44.0 40.6 25-29.9 31.4 26.8 32.9 30.7 20.0 22.5 32.1 24.7 30.4 ≥ 30 21.5 23.4 31.4 16.1 7.0 9.8 21.2 18.4 21.6 Comorbidities, % Diabetes 3.5 1.3 7.0 7.4 2.9 4.3 4.7 2.9 3.9 Heart disease 2.9 1.6 2.2 3.3 1.7 1.8 3.4 1.8 2.9 Lung disease and asthma 12.1 9.2 13.3 11.7 9.0 9.0 9.4 13.6 12.0 Kidney disease 0.7 0.8 1.1 0.9 0.7 0.5 1.1 0.7 0.7 Cancerb 1.4 1.0 1.4 0.8 0.9 1.4 1.1 0.8 1.4 Pregnant (% of females) 1.0 1.2 0.8 1.5 1.3 1.3 1.5 1.1 1.0 Medication usage, % Immunosuppressants 3.4 3.0 4.0 3.6 2.2 2.6 2.9 3.3 3.7 Chemo/Immunotherapy 0.3 0.3 0.2 0.2 0.3 0.3 0.3 0.2 0.3 ACE inhibitor 6.0 2.0 5.9 4.8 2.6 3.4 4.3 3.2 4.8 Aspirinb/NSAIDs 5.9 6.9 7.0 4.0 2.5 3.6 5.6 5.2 5.8 Current smokerb, % 8.3 8.5 11.2 7.9 5.3 7.7 14.9 10.2 10.8 Isolation, % Never left home 5.7 4.8 9.8 6.2 3.4 7.5 5.8 4.8 4.0 Rarely left home 88.0 86.1 80.2 81.6 87.4 83.5 83.2 86.2 89.1 Often left home 6.3 9.0 10.0 12.2 9.2 9.0 10.9 8.9 6.9 Frontline healthcare worker, % 4.7 3.9 10.9 8.5 5.9 11 6.1 4.5 4.5 Community exposure, % Documented 3.1 4.2 7.3 6.1 4.9 9.3 5.1 3.6 3.7 Suspected 9.1 14.8 10.4 9.5 8.3 11.5 10.4 12.4 8.3 Population density, people per sq kmc 4512.0 [805.8,

10223.8]

15448.7 [6785.6, 28932.4]

12702.3 [6892.3, 22592.3]

10558.1 [5097.9, 17620.7]

11442.4 [4906.9, 22290.2]

13270.3 [5754.3, 24413.8]

11939.2 [5613.4, 22247.3]

9243.5 [3186.9, 18059.9]

7730.5 [1930.8, 15917.3]

Income and education Income deprivation 7 [5, 9] 6 [4, 8] 4 [3, 7] 6 [4, 8] 7 [4, 9] 6 [4, 8] 6 [4, 8.25] 6 [4, 9] 6 [4, 9] Education deprivation 7 [5, 9] 8 [5, 9] 6 [4, 8] 7 [5, 9] 8 [6, 9] 7 [5, 9] 8 [5, 9] 7 [5, 9] 7 [5, 9] Abbreviations: ACE, angiotensin converting enzyme; BMI, body mass index; km, kilometer; kg, kilogram; NSAIDs, non-steroidal anti-inflammatory drugs. aMedian [IQR] is presented for continuous variables. Frequencies and proportions are calculated based on the total number of participants with available data. bHistory of cancer, aspirin use, and smoking status have been queried since 3/29/2020 in the U.K. Race and ethnicity questions were queried as of 4/18/2020. cPopulation density was calculated from census data for each Lower Layer Super Output Area.

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Table 2. Risk of a positive Covid-19 test according to race and ethnicity in the United States and the United Kingdom adjusted for comorbidities a. United States Race/Ethnicity White, non-

Hispanic Hispanic/Latinx Black Asian More than one/other race

Individuals testing positive / n 498/147325 89/9251 65/4977 41/6828 23/4774 Age-adjusted OR (95% CI)a 1 (reference) 2.69 (2.14-3.39) 3.69 (2.83-4.81) 1.87 (1.36-2.58) 1.52 (1.00-2.31) Multivariable-adjusted OR (95% CI)b 1 (reference) 2.68 (2.13-3.38) 3.51 (2.68-4.60) 1.97 (1.43-2.73) 1.51 (0.99-2.30) Multivariable-adjusted OR (95% CI) weighted by IPWb 1 (reference) 1.66 (1.18-2.34) 2.49 (1.68-3.69) 1.42 (0.86-2.35) 1.32 (0.67-2.61)

b. United Kingdom Race/Ethnicity White, non-

Hispanic Hispanic/Latinx Black South Asian Chinese East/Southeast Asian Middle Eastern More than

one/other race Individuals testing positive / n 8335/2104829 15/2379 121/13057 485/46350 44/7736 27/2110 82/8466 226/48908 Age-adjusted OR (95% CI)a 1 (reference) 1.42 (0.86-2.36) 2.17 (1.81-2.60) 2.44 (2.23-2.68) 1.30 (0.97-1.75) 2.85 (1.95-4.16) 2.28 (1.83-2.83) 1.23 (1.08-1.40) Multivariable-adjusted OR (95% CI)b 1 (reference) 1.41 (0.85-2.34) 2.10 (1.75-2.51) 2.50 (2.28-2.74) 1.39 (1.03-1.87) 2.93 (2.01-4.28) 2.38 (1.91-2.96) 1.24 (1.09-1.41) Multivariable-adjusted OR (95% CI) weighted by IPWb 1 (reference) 1.71 (0.89-3.27) 1.97 (1.47-2.64) 1.68 (1.43-1.97) 1.79 (1.08-2.96) 1.02 (0.55-1.87) 2.10 (1.52-1.87) 2.10 (1.52-2.91) Abbreviations: CI, confidence interval; OR, odds ratio. aStratified by age and date of entry into the study. bAdjusted for sex, history of diabetes, heart disease, lung disease, kidney disease, and current smoker status (each yes/no), and body mass index (17-18.4, 18.5-24.9, 25-29.9, and ≥30 kg/m2).

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Figure 1. Risk of a positive Covid-19 test according to race and ethnicity in the United States and the United Kingdom with additional adjustment for socioeconomic indices. The multivariable association adjusted for comorbidities, as in Table 2, of race and ethnicity with risk of testing Covid-19 positive in each country is presented (gray). Additional adjustment for isolation (never left home, rarely left home, often left home), frontline healthcare worker (yes/no), community exposure (no, documented, suspected), population density, income, and education in each country, as described in Table 1, demonstrates attenuation of most associations.

Race/ethnicityMultivariable-adjusted

OR (95% CI)Race/ethnicity

Multivariable-adjustedOR (95% CI)

White, non-Hispanic White, non-Hispanic

Hispanic/Latinx Hispanic/Latinx

Black Black

Asian South Asian

More than one/other race Chinese

East/Southeast Asian

■ Multivariable-adjusted Middle Eastern

■ Multivariable + SES-adjusted

More than one/other race

United States United Kingdom

0.5 50.5 5 11

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Table 3. Risk of predicted Covid-19 based on a symptom score according to race and ethnicity in the United States and United Kingdom (pooled). Race/Ethnicity White, non-Hispanic Hispanic/Latinx Black Asian More than one race/other race Individuals testing positive / n 95387/2259841 378/9615 998/18176 3277/63316 3537/63653 Age-adjusted OR (95% CI)a 1 (reference) 1.23 (1.11-1.36) 1.47 (1.38-1.57) 1.15 (1.11-1.19) 1.31 (1.27-1.36) Multivariable-adjusted OR (95% CI)b 1 (reference) 1.22 (1.10-1.36) 1.41 (1.32-1.50) 1.22 (1.18-1.27) 1.31 (1.26-1.35) Multivariable+SES-adjusted OR (95% CI)c 1 (reference) 1.11 (1.00-1.23) 1.17 (1.10-1.25) 1.06 (1.03-1.10) 1.21 (1.17-1.25) Abbreviations: CI, confidence interval; OR, odds ratio. aStratified by age, country, date of entry into the study. bAdjusted for sex, history of diabetes, heart disease, lung disease, kidney disease, and current smoker status (each yes/no), and body mass index (17-18.4, 18.5-24.9, 25-29.9, and ≥30 kg/m2) cFurther adjusted for isolation (never left home, rarely left home, often left home), frontline healthcare worker (yes/no), community exposure to Covid-19 (no, documented, suspected), population density, income, and education in each country (each in quintiles).

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Table 4. Risk of a positive COVID-19 test and seeking or receiving treatment according to race and ethnicity in the United States and the United Kingdom Race/Ethnicity White, non-

Hispanic Hispanic/Latinx Black Asian

More than one race/other race

Covid-19 + visit hospital Individuals testing positive / n 1668/2259841 24/9615 46/18176 116/63316 70/63653 Age-adjusted OR (95% CI)a 1 (reference) 2.36 (1.55-3.59) 3.10 (2.30-4.19) 2.51 (2.08-3.04) 1.72 (1.35-2.18) Multivariable-adjusted OR (95% CI)b 1 (reference) 2.27 (1.49-3.45) 2.71 (2.00-3.66) 2.53 (2.09-3.07) 1.67 (1.32-2.13) Multivariable+SES-adjusted OR (95% CI)c 1 (reference) 1.53 (0.99-2.37) 1.64 (1.20-2.23) 1.58 (1.30-1.92) 1.32 (1.03-1.68) Covid-19 + receive treatment Individuals testing positive / n 764/2259841 8/9615 23/18176 50/63316 27/63653 Age-adjusted OR (95% CI)a 1 (reference) 2.44 (1.18-5.02) 3.66 (2.39-5.60) 2.54 (1.90-3.39) 1.60 (1.09-2.36) Multivariable-adjusted OR (95% CI)b 1 (reference) 2.27 (1.10-4.68) 3.04 (1.98-4.66) 2.48 (1.86-3.31) 1.51 (1.03-2.22) Multivariable+SES-adjusted OR (95% CI)c 1 (reference) 1.34 (0.63-2.88) 1.83 (1.17-2.85) 1.60 (1.19-2.14) 1.18 (0.80-1.74) Abbreviations: CI, confidence interval; OR, odds ratio. aStratified by age, country (in pooled analysis), date of entry into the study. bAdjusted for sex, history of diabetes, heart disease, lung disease, kidney disease, and current smoker status (each yes/no), and body mass index (17-18.4, 18.5-24.9, 25-29.9, and ≥30 kg/m2). cFurther adjusted for isolation (never left home, rarely left home, often left home), frontline healthcare worker (yes/no), community exposure to Covid-19 (no, documented, suspected), population density, income, and education in each country (each in quintiles).

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Racial and ethnic determinants of Covid-19 risk · 6/18/2020 · 2 ABSTRACT Background Racial and...

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